Academic Job Opportunities

Lecturer Part-Time - Temporary

Applications are invited for a Lecturer Part-Time - Temporary position in the Department of Statistics at the University of Washington.

This appointment is for a part-time temporary position, with either a quarterly (September 16 - December 15 for Autumn quarter, December 16 - March 15 for Winter quarter, or March 16 - June 15 for Spring quarter) or a 9-month (September 16 - June 15) service period, depending on departmental needs. 

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Statistics Graders and Tutors

Applications are invited for Graders and Tutors in the Department of Statistics at the University of Washington.

These are hourly appointments open to both undergraduate and graduate students. Appointments are made on a quarterly basis. Current pay rates can be found here.

Graders provide diverse services as course assistants. Duties typically include grading student papers and examinations, consultation with instructors and other duties as assigned.

Tutors provide support and guidance to further undergraduate Statistical education in all introductory Statistics courses. For more information on this program, please visit this page.

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Research Papers

Steven Wilkins Reeves, Shane Lubold, Arun G. Chandrasekhar, Tyler H. McCormick
Published 6/17/2024

The stable unit treatment value assumption states that the outcome of an individual is not affected by the treatment statuses of others, however in many real world applications, treatments can have an effect on many others beyond the immediately treated. Interference can generically be thought of as mediated through…

Keunwoo Lim, Fang Han
Published 6/13/2024

We discuss nonparametric mixing distribution estimation under the Gaussian-smoothed optimal transport (GOT) distance. It is shown that a recently formulated conjecture -- that the Poisson nonparametric maximum likelihood estimator can achieve root-$n$ rate of convergence under the GOT distance -- holds up to some logarithmic terms. We also establish the same conclusion for…

Shreya Prakash, Fan Xia, Elena Erosheva
Published 6/11/2024

Causal discovery methods aim to determine the causal direction between variables using observational data. Functional causal discovery methods, such as those based on the Linear Non-Gaussian Acyclic Model (LiNGAM), rely on structural and distributional assumptions to infer the causal direction. However, approaches for assessing causal discovery methods…

Recent News

We are proud to announce that Statistics Ph.D. student Yikun Zhang has won the student paper award for the ICSA 2024 Applied Statistics Symposium, to be held June 16-19, 2024, in Nashville, Tennessee…
We are proud to announce that Statistics Ph.D. student James Buenfil has won the Theory and Methods student paper competition for the Statistical Methods in Imaging Conference, to be held May 29-31,…
Sunday, May 12 was International Women in Mathematics Day.  International Women in Math Day is celebrated annually on May 12th because that day is the birthday of Maryam Mirzakhan, the first woman (…